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AI data lab for training frontier models and evaluating AI agents.Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more.AI... Show more
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AI data lab for training frontier models and evaluating AI agents.Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more.AI... Show more
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AI data lab for training frontier models and evaluating AI agents.Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more.AI... Show more
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AI data lab for training frontier models and evaluating AI agents.Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more.AI... Show more
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AI data lab for training frontier models and evaluating AI agents.Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more.AI... Show more
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The average salary range is between $ 125,000 and $ 156,000 year , with the average salary hovering around $ 140,500 year .
The average salary range is between $ 109,997 and $ 165,000 year , with the average salary hovering around $ 129,990 year .
mechanical engineering
technical document analysis
problem-solving
written and verbal communication
data analysis
attention to detail
self-management
interdisciplinary collaboration
technical content creation
data quality assurance
micro1 is the leading AI data lab for training frontier models and evaluating AI agents. Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more. micro1 transforms that real-world expertise into high-quality training data, evaluations, and feedback loops that improve how AI systems learn, reason, and perform.
Our platform identifies and vets top talent through an AI recruiter, enabling high-quality expert contributions at scale. We aim to enable 1 billion people to do meaningful work by applying their expertise to AI. As our global expert network grows, micro1 is building the human intelligence layer for frontier AI.
Job Title: Mechanical Engineer
Job Type: Contractor
Location: Remote
Rate: 20$-50$ per task
Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Key Responsibilities:
• Analyze technical documents and extract key information relevant to your domain expertise
• Generate, review, and refine questions and solutions based on real-world mechanical engineering scenarios
• Collaborate with multidisciplinary teams to ensure accuracy and depth of data and analysis
• Provide detailed written and verbal feedback on document clarity, technical accuracy, and effectiveness
• Apply advanced subject matter knowledge to evaluate and solve complex engineering problems
• Work independently, managing your time to deliver high-quality outputs with minimal supervision
• Contribute to the continuous improvement of data quality and project processes
Required Skills and Qualifications:
• 2-6 years of professional or academic experience in mechanical engineering or a closely related field (lab, workplace, or academia)
• Strong reading comprehension skills, with proven ability to analyze and interpret technical documents
• Exceptional English communication skills, both written and verbal
• Demonstrated experience in creating or evaluating technical content, such as reports, studies, or problem sets
• Ability to work independently and efficiently, with excellent self-management
• High attention to detail and commitment to data accuracy
• Experience interfacing with technical documentation and performing analytical tasks
Preferred Qualifications:
• Advanced degree (Master’s or PhD) in Mechanical Engineering, Chemistry, Physics, or Biology
• Previous experience contributing to interdisciplinary or research-driven projects
• Familiarity with data-driven analysis or training data preparation
